DataAnalysisAndVisualisation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "***Installing justpy (library for building web apps and data visualization):***"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "!pip3 install justpy"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Collecting justpy\n",
      "  Using cached justpy-0.1.5-py3-none-any.whl (4.4 MB)\n",
      "Collecting addict>=2.2.1\n",
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      "Collecting httpx>=0.11.0\n",
      "  Using cached httpx-0.18.2-py3-none-any.whl (76 kB)\n",
      "Requirement already satisfied: jinja2>=2.10.1 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from justpy) (2.10.1)\n",
      "Collecting demjson>=2.2.4\n",
      "  Using cached demjson-2.2.4.tar.gz (131 kB)\n",
      "Collecting starlette>=0.12.0\n",
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      "Collecting aiofiles\n",
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      "Collecting uvicorn>=0.7.1\n",
      "  Using cached uvicorn-0.14.0-py3-none-any.whl (50 kB)\n",
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      "Requirement already satisfied: idna>=2.8 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from anyio==3.*->httpcore<0.14.0,>=0.13.3->httpx>=0.11.0->justpy) (2.8)\n",
      "Collecting typing-extensions\n",
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      "Requirement already satisfied: colorama in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from click>=7.*->uvicorn>=0.7.1->justpy) (0.4.1)\n",
      "Collecting importlib-metadata\n",
      "  Downloading importlib_metadata-4.6.1-py3-none-any.whl (17 kB)\n",
      "Collecting zipp>=0.5\n",
      "  Downloading zipp-3.5.0-py3-none-any.whl (5.7 kB)\n",
      "Using legacy 'setup.py install' for demjson, since package 'wheel' is not installed.\n",
      "Installing collected packages: zipp, typing-extensions, sniffio, rfc3986, importlib-metadata, h11, anyio, httpcore, click, asgiref, websockets, uvicorn, starlette, itsdangerous, httpx, demjson, aiofiles, addict, justpy\n",
      "    Running setup.py install for demjson: started\n",
      "    Running setup.py install for demjson: finished with status 'done'\n",
      "Successfully installed addict-2.4.0 aiofiles-0.7.0 anyio-3.2.1 asgiref-3.4.1 click-8.0.1 demjson-2.2.4 h11-0.12.0 httpcore-0.13.6 httpx-0.18.2 importlib-metadata-4.6.1 itsdangerous-2.0.1 justpy-0.1.5 rfc3986-1.5.0 sniffio-1.2.0 starlette-0.15.0 typing-extensions-3.10.0.0 uvicorn-0.14.0 websockets-9.1 zipp-3.5.0\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "***Installing matplotlib (library for quick data visualization):***"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "!pip3 install matplotlib"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Requirement already satisfied: matplotlib in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (3.4.2)\n",
      "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from matplotlib) (8.3.0)\n",
      "Requirement already satisfied: numpy>=1.16 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from matplotlib) (1.21.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from matplotlib) (2.8.0)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from matplotlib) (0.10.0)\n",
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      "Requirement already satisfied: six in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from cycler>=0.10->matplotlib) (1.12.0)\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "***Installing pandas (library for data analysis):***"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "!pip3 install pandas"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Requirement already satisfied: pandas in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (1.2.5)\n",
      "Requirement already satisfied: numpy>=1.16.5 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from pandas) (1.21.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from pandas) (2.8.0)\n",
      "Requirement already satisfied: pytz>=2017.3 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from pandas) (2021.1)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (from python-dateutil>=2.7.3->pandas) (1.12.0)\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "***Installing pytz (library for datetime calculations between timezones):***"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "!pip3 install pytz"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Requirement already satisfied: pytz in c:\\users\\simon\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages (2021.1)\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 1. Overview of the Data Frame ##"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "source": [
    "import pandas as pd\r\n",
    "import matplotlib.pyplot as plt\r\n",
    "from datetime import datetime\r\n",
    "from pytz import utc  # Needed to support dtype=datetime64[ns, UTC] from Pandas and datetime.datetime comparison\r\n",
    "data = pd.read_csv('assets/csv/reviews.csv', parse_dates=['Timestamp'])  # Timestamp column is parsed as text otherwise\r\n",
    "data.head()  # first 5 rows of the data file"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                         Course Name  \\\n",
       "0  The Python Mega Course: Build 10 Real World Ap...   \n",
       "1  The Python Mega Course: Build 10 Real World Ap...   \n",
       "2  The Python Mega Course: Build 10 Real World Ap...   \n",
       "3  The Python Mega Course: Build 10 Real World Ap...   \n",
       "4  The Python Mega Course: Build 10 Real World Ap...   \n",
       "\n",
       "                  Timestamp  Rating Comment  \n",
       "0 2021-04-02 06:25:52+00:00     4.0     NaN  \n",
       "1 2021-04-02 05:12:34+00:00     4.0     NaN  \n",
       "2 2021-04-02 05:11:03+00:00     4.0     NaN  \n",
       "3 2021-04-02 03:33:24+00:00     5.0     NaN  \n",
       "4 2021-04-02 03:31:49+00:00     4.5     NaN  "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Course Name</th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 06:25:52+00:00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 05:12:34+00:00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 05:11:03+00:00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 03:33:24+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 03:31:49+00:00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 29
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "data.shape"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(45000, 4)"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "data.columns"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Index(['Course Name', 'Timestamp', 'Rating', 'Comment'], dtype='object')"
      ]
     },
     "metadata": {},
     "execution_count": 7
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "source": [
    "data.hist('Rating')"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'Rating'}>]], dtype=object)"
      ]
     },
     "metadata": {},
     "execution_count": 8
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 2. Selecting data from the Data Frame ##"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Select a column ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "source": [
    "data['Rating']"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "0        4.0\n",
       "1        4.0\n",
       "2        4.0\n",
       "3        5.0\n",
       "4        4.5\n",
       "        ... \n",
       "44995    4.0\n",
       "44996    5.0\n",
       "44997    5.0\n",
       "44998    5.0\n",
       "44999    5.0\n",
       "Name: Rating, Length: 45000, dtype: float64"
      ]
     },
     "metadata": {},
     "execution_count": 9
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "source": [
    "data['Rating'].mean()  # Mean value of the column"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "4.442155555555556"
      ]
     },
     "metadata": {},
     "execution_count": 10
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Select multiple columns ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "source": [
    "data[['Course Name', 'Rating']]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                             Course Name  Rating\n",
       "0      The Python Mega Course: Build 10 Real World Ap...     4.0\n",
       "1      The Python Mega Course: Build 10 Real World Ap...     4.0\n",
       "2      The Python Mega Course: Build 10 Real World Ap...     4.0\n",
       "3      The Python Mega Course: Build 10 Real World Ap...     5.0\n",
       "4      The Python Mega Course: Build 10 Real World Ap...     4.5\n",
       "...                                                  ...     ...\n",
       "44995                 Python for Beginners with Examples     4.0\n",
       "44996  The Python Mega Course: Build 10 Real World Ap...     5.0\n",
       "44997  The Python Mega Course: Build 10 Real World Ap...     5.0\n",
       "44998                 Python for Beginners with Examples     5.0\n",
       "44999  The Python Mega Course: Build 10 Real World Ap...     5.0\n",
       "\n",
       "[45000 rows x 2 columns]"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Course Name</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44995</th>\n",
       "      <td>Python for Beginners with Examples</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44996</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44997</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44998</th>\n",
       "      <td>Python for Beginners with Examples</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44999</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45000 rows × 2 columns</p>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 11
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Select a row ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "source": [
    "data.iloc[3]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Course Name    The Python Mega Course: Build 10 Real World Ap...\n",
       "Timestamp                              2021-04-02 03:33:24+00:00\n",
       "Rating                                                       5.0\n",
       "Comment                                                      NaN\n",
       "Name: 3, dtype: object"
      ]
     },
     "metadata": {},
     "execution_count": 12
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Selecting Multiple rows ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "source": [
    "data.iloc[1:3]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                         Course Name  \\\n",
       "1  The Python Mega Course: Build 10 Real World Ap...   \n",
       "2  The Python Mega Course: Build 10 Real World Ap...   \n",
       "\n",
       "                   Timestamp  Rating Comment  \n",
       "1  2021-04-02 05:12:34+00:00     4.0     NaN  \n",
       "2  2021-04-02 05:11:03+00:00     4.0     NaN  "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Course Name</th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 05:12:34+00:00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 05:11:03+00:00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 13
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Selecting a section ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "source": [
    "data[['Course Name', 'Rating']].iloc[1:3]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                         Course Name  Rating\n",
       "1  The Python Mega Course: Build 10 Real World Ap...     4.0\n",
       "2  The Python Mega Course: Build 10 Real World Ap...     4.0"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Course Name</th>\n",
       "      <th>Rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 14
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Selecting a cell ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "source": [
    "data['Timestamp'].iloc[2]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "'2021-04-02 05:11:03+00:00'"
      ]
     },
     "metadata": {},
     "execution_count": 15
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "source": [
    "type(data['Timestamp'].iloc[2])"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "metadata": {},
     "execution_count": 16
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "source": [
    "data['Rating'].iloc[2]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "4.0"
      ]
     },
     "metadata": {},
     "execution_count": 17
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "source": [
    "type(data['Rating'].iloc[2])"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "numpy.float64"
      ]
     },
     "metadata": {},
     "execution_count": 18
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "***Alternative method***"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "source": [
    "data.at[2, 'Rating']"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "4.0"
      ]
     },
     "metadata": {},
     "execution_count": 19
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 3. Filtering Data based on conditions ##"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### One condition ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "source": [
    "data[data['Rating'] > 4]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                             Course Name  \\\n",
       "3      The Python Mega Course: Build 10 Real World Ap...   \n",
       "4      The Python Mega Course: Build 10 Real World Ap...   \n",
       "5      The Python Mega Course: Build 10 Real World Ap...   \n",
       "6      The Python Mega Course: Build 10 Real World Ap...   \n",
       "7      The Python Mega Course: Build 10 Real World Ap...   \n",
       "...                                                  ...   \n",
       "44994  The Python Mega Course: Build 10 Real World Ap...   \n",
       "44996  The Python Mega Course: Build 10 Real World Ap...   \n",
       "44997  The Python Mega Course: Build 10 Real World Ap...   \n",
       "44998                 Python for Beginners with Examples   \n",
       "44999  The Python Mega Course: Build 10 Real World Ap...   \n",
       "\n",
       "                       Timestamp  Rating Comment  \n",
       "3      2021-04-02 03:33:24+00:00     5.0     NaN  \n",
       "4      2021-04-02 03:31:49+00:00     4.5     NaN  \n",
       "5      2021-04-02 01:10:06+00:00     4.5     NaN  \n",
       "6      2021-04-02 00:44:54+00:00     4.5     NaN  \n",
       "7      2021-04-01 23:42:02+00:00     5.0     NaN  \n",
       "...                          ...     ...     ...  \n",
       "44994  2018-01-01 01:19:24+00:00     5.0     NaN  \n",
       "44996  2018-01-01 01:09:56+00:00     5.0     NaN  \n",
       "44997  2018-01-01 01:08:11+00:00     5.0     NaN  \n",
       "44998  2018-01-01 01:05:26+00:00     5.0     NaN  \n",
       "44999  2018-01-01 01:01:16+00:00     5.0     NaN  \n",
       "\n",
       "[29758 rows x 4 columns]"
      ],
      "text/html": [
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       "      <th>Course Name</th>\n",
       "      <th>Timestamp</th>\n",
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       "      <th>Comment</th>\n",
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       "      <th>3</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 03:33:24+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 03:31:49+00:00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 01:10:06+00:00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 00:44:54+00:00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-01 23:42:02+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>44994</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2018-01-01 01:19:24+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44996</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2018-01-01 01:09:56+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44997</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2018-01-01 01:08:11+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44998</th>\n",
       "      <td>Python for Beginners with Examples</td>\n",
       "      <td>2018-01-01 01:05:26+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44999</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2018-01-01 01:01:16+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29758 rows × 4 columns</p>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 20
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "source": [
    "data[data['Rating'] > 4].count()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Course Name    29758\n",
       "Timestamp      29758\n",
       "Rating         29758\n",
       "Comment         4927\n",
       "dtype: int64"
      ]
     },
     "metadata": {},
     "execution_count": 21
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "***Filtering all rows with a rating > 4 and show only the rating column***"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "source": [
    "data[data['Rating'] > 4]['Rating']"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "3        5.0\n",
       "4        4.5\n",
       "5        4.5\n",
       "6        4.5\n",
       "7        5.0\n",
       "        ... \n",
       "44994    5.0\n",
       "44996    5.0\n",
       "44997    5.0\n",
       "44998    5.0\n",
       "44999    5.0\n",
       "Name: Rating, Length: 29758, dtype: float64"
      ]
     },
     "metadata": {},
     "execution_count": 22
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Multiple conditions ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "source": [
    "data[(data['Rating'] > 4) & (data['Course Name'] == 'The Complete Python Course: Build 10 Professional OOP Apps')]"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                            Course Name  \\\n",
       "31    The Complete Python Course: Build 10 Professio...   \n",
       "34    The Complete Python Course: Build 10 Professio...   \n",
       "43    The Complete Python Course: Build 10 Professio...   \n",
       "45    The Complete Python Course: Build 10 Professio...   \n",
       "101   The Complete Python Course: Build 10 Professio...   \n",
       "...                                                 ...   \n",
       "2501  The Complete Python Course: Build 10 Professio...   \n",
       "2502  The Complete Python Course: Build 10 Professio...   \n",
       "2509  The Complete Python Course: Build 10 Professio...   \n",
       "2523  The Complete Python Course: Build 10 Professio...   \n",
       "2525  The Complete Python Course: Build 10 Professio...   \n",
       "\n",
       "                      Timestamp  Rating Comment  \n",
       "31    2021-04-01 01:32:52+00:00     5.0     NaN  \n",
       "34    2021-03-31 22:53:04+00:00     5.0     NaN  \n",
       "43    2021-03-31 19:15:25+00:00     5.0     NaN  \n",
       "45    2021-03-31 17:23:15+00:00     5.0     NaN  \n",
       "101   2021-03-29 21:54:00+00:00     4.5     NaN  \n",
       "...                         ...     ...     ...  \n",
       "2501  2021-01-14 21:19:44+00:00     4.5     NaN  \n",
       "2502  2021-01-14 20:57:14+00:00     5.0     NaN  \n",
       "2509  2021-01-14 15:46:18+00:00     5.0     NaN  \n",
       "2523  2021-01-13 22:21:14+00:00     5.0     NaN  \n",
       "2525  2021-01-13 20:44:02+00:00     5.0     NaN  \n",
       "\n",
       "[351 rows x 4 columns]"
      ],
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       "      <td>The Complete Python Course: Build 10 Professio...</td>\n",
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       "      <td>The Complete Python Course: Build 10 Professio...</td>\n",
       "      <td>2021-03-31 19:15:25+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>45</th>\n",
       "      <td>The Complete Python Course: Build 10 Professio...</td>\n",
       "      <td>2021-03-31 17:23:15+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>The Complete Python Course: Build 10 Professio...</td>\n",
       "      <td>2021-03-29 21:54:00+00:00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2501</th>\n",
       "      <td>The Complete Python Course: Build 10 Professio...</td>\n",
       "      <td>2021-01-14 21:19:44+00:00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2502</th>\n",
       "      <td>The Complete Python Course: Build 10 Professio...</td>\n",
       "      <td>2021-01-14 20:57:14+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2509</th>\n",
       "      <td>The Complete Python Course: Build 10 Professio...</td>\n",
       "      <td>2021-01-14 15:46:18+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2523</th>\n",
       "      <td>The Complete Python Course: Build 10 Professio...</td>\n",
       "      <td>2021-01-13 22:21:14+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2525</th>\n",
       "      <td>The Complete Python Course: Build 10 Professio...</td>\n",
       "      <td>2021-01-13 20:44:02+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>351 rows × 4 columns</p>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 23
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "source": [
    "data[(data['Rating'] > 4) & (data['Course Name'] == 'The Complete Python Course: Build 10 Professional OOP Apps')].mean()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Rating    4.908832\n",
       "dtype: float64"
      ]
     },
     "metadata": {},
     "execution_count": 24
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 4. Time Based Filtering ##"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "source": [
    "data[(data['Timestamp'] >= datetime(2020, 7, 1, tzinfo=utc)) & (data['Timestamp'] <= datetime(2020, 12, 31, tzinfo=utc))]  # add tzinfo=utc to enforece the correct datetime dtype"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                            Course Name  \\\n",
       "3065  Interactive Data Visualization with Python and...   \n",
       "3066  The Python Mega Course: Build 10 Real World Ap...   \n",
       "3067  The Python Mega Course: Build 10 Real World Ap...   \n",
       "3068  The Python Mega Course: Build 10 Real World Ap...   \n",
       "3069  The Python Mega Course: Build 10 Real World Ap...   \n",
       "...                                                 ...   \n",
       "9729  The Python Mega Course: Build 10 Real World Ap...   \n",
       "9730  The Python Mega Course: Build 10 Real World Ap...   \n",
       "9731  The Python Mega Course: Build 10 Real World Ap...   \n",
       "9732  The Python Mega Course: Build 10 Real World Ap...   \n",
       "9733  The Python Mega Course: Build 10 Real World Ap...   \n",
       "\n",
       "                     Timestamp  Rating  \\\n",
       "3065 2020-12-30 23:28:34+00:00     3.0   \n",
       "3066 2020-12-30 22:59:02+00:00     4.0   \n",
       "3067 2020-12-30 22:40:10+00:00     4.5   \n",
       "3068 2020-12-30 21:56:41+00:00     4.5   \n",
       "3069 2020-12-30 21:14:34+00:00     4.5   \n",
       "...                        ...     ...   \n",
       "9729 2020-07-01 03:09:44+00:00     3.5   \n",
       "9730 2020-07-01 03:09:12+00:00     5.0   \n",
       "9731 2020-07-01 02:40:58+00:00     4.0   \n",
       "9732 2020-07-01 02:04:02+00:00     5.0   \n",
       "9733 2020-07-01 00:01:34+00:00     2.0   \n",
       "\n",
       "                                                Comment  \n",
       "3065                                                NaN  \n",
       "3066                                                NaN  \n",
       "3067                                                NaN  \n",
       "3068                                                NaN  \n",
       "3069                                                NaN  \n",
       "...                                                 ...  \n",
       "9729                                                NaN  \n",
       "9730                                                NaN  \n",
       "9731                                                NaN  \n",
       "9732                                               nice  \n",
       "9733  Hard to follow if u have no experience program...  \n",
       "\n",
       "[6669 rows x 4 columns]"
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       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3068</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2020-12-30 21:56:41+00:00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3069</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2020-12-30 21:14:34+00:00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9729</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2020-07-01 03:09:44+00:00</td>\n",
       "      <td>3.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9730</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2020-07-01 03:09:12+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9731</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2020-07-01 02:40:58+00:00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9732</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2020-07-01 02:04:02+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>nice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9733</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2020-07-01 00:01:34+00:00</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Hard to follow if u have no experience program...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6669 rows × 4 columns</p>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 30
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 5. From Data to Information ##"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "source": [
    "data.head()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                         Course Name  \\\n",
       "0  The Python Mega Course: Build 10 Real World Ap...   \n",
       "1  The Python Mega Course: Build 10 Real World Ap...   \n",
       "2  The Python Mega Course: Build 10 Real World Ap...   \n",
       "3  The Python Mega Course: Build 10 Real World Ap...   \n",
       "4  The Python Mega Course: Build 10 Real World Ap...   \n",
       "\n",
       "                  Timestamp  Rating Comment  \n",
       "0 2021-04-02 06:25:52+00:00     4.0     NaN  \n",
       "1 2021-04-02 05:12:34+00:00     4.0     NaN  \n",
       "2 2021-04-02 05:11:03+00:00     4.0     NaN  \n",
       "3 2021-04-02 03:33:24+00:00     5.0     NaN  \n",
       "4 2021-04-02 03:31:49+00:00     4.5     NaN  "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Course Name</th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Rating</th>\n",
       "      <th>Comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 06:25:52+00:00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 05:12:34+00:00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 05:11:03+00:00</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 03:33:24+00:00</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Python Mega Course: Build 10 Real World Ap...</td>\n",
       "      <td>2021-04-02 03:31:49+00:00</td>\n",
       "      <td>4.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 38
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Average Rating ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "source": [
    "data['Rating'].mean()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "4.442155555555556"
      ]
     },
     "metadata": {},
     "execution_count": 31
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Average Rating for a Particular Course ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "source": [
    "data[data['Course Name'] == 'The Python Mega Course: Build 10 Real World Applications']['Rating'].mean()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "4.477270180942244"
      ]
     },
     "metadata": {},
     "execution_count": 32
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Average Rating for a particular period ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "source": [
    "data[(data['Timestamp'] >= datetime(2020, 1, 1, tzinfo=utc)) & (data['Timestamp'] <= datetime(2020, 12, 31, tzinfo=utc))]['Rating'].mean()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "4.476541271662339"
      ]
     },
     "metadata": {},
     "execution_count": 34
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Average Rating for a particular period for a particular course ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "source": [
    "data[\r\n",
    "    (data['Timestamp'] >= datetime(2020, 1, 1, tzinfo=utc)) &\r\n",
    "    (data['Timestamp'] <= datetime(2020, 12, 31, tzinfo=utc)) &\r\n",
    "    (data['Course Name'] == 'The Python Mega Course: Build 10 Real World Applications')\r\n",
    "]['Rating'].mean()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "4.506076089208037"
      ]
     },
     "metadata": {},
     "execution_count": 37
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Average of uncommented ratings ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "source": [
    "data[\r\n",
    "    data['Comment'].isnull()\r\n",
    "]['Rating'].mean()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "4.433679746603492"
      ]
     },
     "metadata": {},
     "execution_count": 39
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Average of commented ratings ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "source": [
    "data[\r\n",
    "    data['Comment'].notnull()\r\n",
    "]['Rating'].mean()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "4.489777908515959"
      ]
     },
     "metadata": {},
     "execution_count": 40
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Number of uncommented ratings ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "source": [
    "data[\r\n",
    "    data['Comment'].isnull()\r\n",
    "]['Rating'].count()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "38201"
      ]
     },
     "metadata": {},
     "execution_count": 41
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Number of commented ratings ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "source": [
    "data[\r\n",
    "    data['Comment'].notnull()\r\n",
    "]['Rating'].count()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "6799"
      ]
     },
     "metadata": {},
     "execution_count": 42
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Number of comments containing a certain word ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "source": [
    "data[\r\n",
    "    data['Comment'].str.contains('accent', na=False)  # str can't handle null values\r\n",
    "]['Comment'].count()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "77"
      ]
     },
     "metadata": {},
     "execution_count": 45
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Average of commented ratings with \"accent\" in comment ###"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "source": [
    "data[\r\n",
    "    data['Comment'].str.contains('accent', na=False)  # str can't handle null values\r\n",
    "]['Rating'].mean()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "3.8636363636363638"
      ]
     },
     "metadata": {},
     "execution_count": 46
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  }
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